The present invention relates to medical ultrasonic imaging, and in particular to systems that adaptively set one or more stages of back-end mapping that may include gain, dynamic range and post-processing map stages in one or more image dimensions to improve such imaging.
In conventional ultrasonic imaging, a B-mode signal is adjusted for gain and dynamic range before it is mapped to a range of gray levels or colors for display. The dynamic range of the signal to be displayed can conventionally be set by the user by means of a display dynamic range control. This control is conventionally independent of range and azimuthal position in the image. The gain can conventionally be varied by the user using a depth gain compensation (DGC) or a time gain compensation (TGC) control along with the master gain or B gain control. The DGC and TGC controls are conventionally variable in range (axial dimension) only, and the master gain is independent of both range and lateral (azimuthal) position. A few systems also offer lateral gain compensation in addition to depth gain compensation, but the two one-dimensional gain controls comprise only an approximation to a true two-dimensional gain control.
After gain and display dynamic range have been applied, log-compressed B-mode signals are re-quantized, typically to 8-bit or 256 quantization levels. The quantization step (in dB) is given by the ratio of the dynamic range selected by the user to the number of quantization levels. After quantization, a post-processing map is used to map the quantization levels to a range of gray levels or colors. This map can be a selected one of a predesigned set of maps or alternately a user-designed map. These maps are also conventionally range and azimuth independent.
On commercially available ultrasound imaging systems, gain controls are often used by the users to adjust the brightness level. In many cases, users adjust the gain mainly to keep the regional mean of the soft tissue gray level within a narrow range of gray values across the image. This preferred range is consistent from user to user, and in many cases users tend to adjust the gain to set the gray level for soft tissue roughly to the 64th gray level on a linear map that maps 0 to black and 255 to white. However, gain adjustments for soft tissue brightness level and uniformity do not simultaneously optimize noise suppression and prevent display saturation. For this reason, gain and/or dynamic range are frequently sub-optimal for some or all parts of an image. As a result, information can be lost by cutting off low-level signals or saturating high-level signals.
Such loss of information due to errors in setting gain and/or dynamic range can be reduced or eliminated by setting the dynamic range to a very high level. This approach however reduces contrast resolution because different tissue types are then mapped to similar gray levels, thereby reducing the prominence of echogenicity differences.
U.S. Pat. No. 5,579,768 to Klesenski (assigned to the assignee of the present invention) proposes an automatic gain compensation system that uses B-mode intensity of image signals to identify regions of soft tissue, and then automatically sets these regions of soft tissue to a predetermined magnitude.
U.S. Pat. No. 5,993,392 to Roundhill discloses an ultrasonic imaging system in which dynamic range is selected based upon the range and azimuthal position of the image signal within the frame. The disclosed system is not responsive to the image signal itself, and therefore cannot be considered to be an adaptive system. Rather, the approach used in the Roundhill patent is to select a stored compression map as a function of the range and azimuth of the display signal.
Conventional ultrasound imaging systems use various control stages in the backend to map a range (window) of input signal levels to a range of display gray levels or colors. These stages may include a single or multiple gain stages, a dynamic range control stage, post processing maps, etc. The dynamic range control allows users to adjust the width of the window of input signal levels to be displayed. We will refer to this user control as the display dynamic range control to differentiate it from other possible windowing operations a system might have. The gain controls let the user adjust the position of this window. Therefore, the dynamic range and gain stages together determine the actual window of input signal levels to be displayed without saturation. A post-processing map then determines the actual gray levels and or colors that correspond to the signal levels thus selected for display.
Ideally, the display dynamic range should be set equal to the dynamic range of the input signal, and the gain should be set to match the full range of input signal to the full range of displayed values. In this way, no signal is lost and the back-end quantization noise is minimized. In addition, the regional mean of the soft tissue signal should be mapped to a particular display level (e.g., gray level) uniformly across the image for display uniformity.
The dynamic range of a B-mode signal is determined by the noise level of the system and the maximum echo level. The noise level of the system is range and azimuth dependent, due to range and azimuth dependent front-end gain and imager aperture size. The maximum echo level is determined by the transmit field strength, the attenuation of the medium, the reflectivity of the object being observed, and the coherent gain of the receive beamformer. For these reasons, an adaptive and multi-dimensional back-end mapping stage or stages are required to achieve the above-mentioned mapping goals.
We here describe an adaptive and multi-dimensional method that a) prevents loss of information in the back-end, b) reduces or eliminates electronic noise in the displayed images, c) minimizes the back-end quantization noise and d) for B-mode, maps the regional mean of soft tissue to a programmable target display level for tissue. We also describe several reduced implementations that satisfy a subset of the above list. The reduced implementations adaptively adjust gain and in some cases dynamic range in two dimensions to display images substantially free of electronic noise and to display tissue at a target tissue gray level.
Note that the term xe2x80x9cinput signalxe2x80x9d is used broadly to refer to amplitude, intensity or log-compressed amplitude of the beamformer output (i.e. B-mode signal) as well as to any parameter of interest derived or extracted from the beamformer output, including the average velocity and power estimates of the Doppler frequency shift (i.e. Color Doppler Mode signals) and the power spectrum estimate of the Doppler frequency shift (i.e., Spectral Doppler Mode signals). The foregoing paragraphs have been provided by way of introduction, and they are not intended to limit the scope of the following claims.
FIG. 1 is a block diagram of a medical diagnostic ultrasonic imaging system that incorporates a preferred embodiment of this invention.
FIG. 2 is a block diagram of a first preferred embodiment of the multi-dimensional back-end mapping stage of FIG. 1.
FIG. 3 is a block diagram of a modification to the embodiment of FIG. 2.
FIGS. 4, 5, and 6 are graphs used to illustrate alternative mapping functions performed by the embodiment of FIG. 2.
FIG. 7 is a flow chart of a method performed by the embodiment of FIG. 2.
FIG. 8 is a block diagram of another embodiment of the adaptive multidimensional back-end mapping stage of FIG. 1.
FIG. 9 is a more detailed block diagram of a first preferred embodiment of the mapping stage of FIG. 8.
FIG. 10 is a flowchart of a method implemented by the embodiment of FIG. 9.
FIGS. 11, 12 and 13 are graphs illustrating operation of the embodiment of FIG. 9.
FIG. 14 is a block diagram of a second preferred embodiment of the gain processor of FIG. 8, which operates to set both local gain and local dynamic range adaptively.
FIG. 15 is a block diagram of a third embodiment of the gain processor of FIG. 8, which operates to set both the local gain and the local dynamic range adaptively.
FIG. 16 is a graph used to explain operation of the embodiment of FIG. 15.